首页 | 本学科首页   官方微博 | 高级检索  
     检索      

TSK模糊模型的GA—BP混合学习方法
引用本文:谢卫华,刘建成,周晓光,蒋新华.TSK模糊模型的GA—BP混合学习方法[J].长沙铁道学院学报,2010(1):93-96.
作者姓名:谢卫华  刘建成  周晓光  蒋新华
作者单位:[1]中南大学信息科学与工程学院,湖南长沙410075 [2]江苏蓝深远望系统集成有限公司,江苏无锡214001
基金项目:基金项目:湖南省自然科学基金资助项目(04JJY6036)
摘    要:针对TSK模糊模型的学习是多约束和多目标优化问题,提出一种基于GA—BP的TSK模糊模型学习方法。论述了所涉及的相关问题,包括模型结构的种群编码、进化策略及其适应值评估策略,推导了在进化过程中模糊模型前件和后件参数的BP算法。仿真结果表明:该方法具有先验知识要求少、获取的模型具有较好的精确性和简洁性等特点。

关 键 词:TSK模糊模型  遗传算法  BP算法

Learning TSK fuzzy model by GA- BP method
XIE Wei-hua,LIU Jian-cheng,ZHOU Xiao-guang,JIANG Xin-hua.Learning TSK fuzzy model by GA- BP method[J].Journal of Changsha Railway University,2010(1):93-96.
Authors:XIE Wei-hua  LIU Jian-cheng  ZHOU Xiao-guang  JIANG Xin-hua
Institution:(School of Information Science and Engineering, Central South University, Changsha 410075, China; 2. Jiangsu Lanshen Yuanwang System Integration Limited Company, Wuxi 214001, China)
Abstract:Due to the TSK fuzzy model is multi -constraint and multi -target optimization which is difficult to learn, GA - BP hybrid learning method for the model was proposed. Some problems related to a species coding means for the model structure, evolution and fitness evaluation strategy were discussed. The error back propaga- tion algorithm (BP) for training the antecedent and consequent parameters during the process of evolution was derived. The results show that the learning method has the properties of less previous information about objects, better compaction and accuracy for the model.
Keywords:TSK fuzzy model  genetic algorithms  BP algorithm
本文献已被 维普 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号